Wednesday, November 09, 2016

He was a Swiss astrologer in the early 20th century. Krafft correctly predicted that Hitler would be in danger between November 7 and November 10, 1939, and wrote to a friend working for Himmler, warning him of an attempt on Hitler’s life. After a bomb exploded in the Munich beer hall November 8, barely missing Hitler, Krafft became a favorite with the Nazis and was made their court astrologer. However, when towards the end of the war, he (correctly) predicted that bombs would soon destroy the Propaganda ministry in Berlin, he was viewed as a traitor. He was put into jail, and died of typhus on the journey to the Buchenwald concentration camp.

Reading the final blog post of famed election forecaster Nate Silver on his fivethirtyeightblog, he says 10.41AM on election day morning of Nov 8, 2016 “…..Clinton is a 71 percent favorite to win the election according to our polls-only model and a 72 percent favorite according to our polls-plus model…..”
Next morning Hillary Clinton conceded defeat to right-wing populist Donald Trump.

Donald Trump is only the last in a long list of populist leaders swaying public opinion, where “ordinary” people are afraid to admit their preferences, leading conventional pollsters astray. I still remember a visit together with my colleague Manfred Vogel to the offices of highly respected Swiss pollster Claude Longchamp. At that time Longchamp was reeling from a similarly spectacular mis-prediction, where he had forecast a clear rejection of a Swiss National referendum to forbid construction of minaret towers for mosques in Switzerland (the “Minaret Initiative”), only to see the Swiss voters clearly approving this restrictive clause. In my own social media analysis on Twitter, Facebook, and blogs, using an early version of the six honest signals of communication I had identified a surprisingly strong showing for the Minaret Initiative well before the election.

The explanation for the surprising success of the “Minaret Initiative”, Brexit, and Donald Trump, is that “ordinary” people are afraid to express their true beliefs when asked in phone polls. In a silent revolution of the disenfranchised, they lie to the pollsters, to only voice what they really believe on election day. The social network created using our galaxyscope tool through analyzing Wikipedia links, blog links, and re-tweet follower networks illustrates this point. Donald Trump - for all his billionaire bluster - is a clear outsider, and underdog of the establishment. Many people therefore will be reluctant to tell their preference for Trump to the pollsters.

The "ordinary" people will however tell what they really think on social media to their friends, so interpreting their “honest signals” would be a better way than asking on the phone. This analysis is extremely hard and time consuming, because social media usage and popularity of particular tools change year by year. It used to be that Facebook posts could be easily read by anybody – not anymore. It used to be that Chileans used to express themselves on Twitter – not anymore. In the age of Snapchat, Whatsapp, WeChat, Instagram, and legions of other point-to-point communication tools it gets near to impossible to collect this datastream (well, maybe there might be a hidden backdoor if you are NSA, but not for ordinary researchers). Therefore, the art and science of prediction is now to interpret publicly available sources such as Google and Wikipedia search logs, blog posts, Tweets, Wikipedia pages, and online news articles, and disentangle their honest signals from the straightforward network picture shown above.

However, as Karl Ernst Krafft illustrates, predicting the outcome of politics can be extremely costly for the one doing the prediction. Frequently the messenger will be shot. So no political prediction this time!

Thanks to Alain Egli from GDI for pointing me to the nice picture illustrating embeddedness of Hillary Clinton compared to Donald Trump

Sunday, August 07, 2016

If all we want is money, power, and glory, the world becomes a sad place. Academic research provides solid evidence that the pursuit of these three things makes collaboration among humans miserable.

For instance, it appears that students of management and economics, who make the pursuit of money and power their life's goal, are more greedy even
before they start their studies, and that they become even more so over the
course of their education.In behavioral
research, first year economics students have been shown to be more likely to
free-ride in public goods games: In one experiment, students could deposit money into a public account where it was multiplied and
distributed to all participants, or keep their money in a private account, and
still participate in the distribution of the public pool.First year graduate students in economics
kept eighty percent of the money for themselves, and only put twenty percent
into the public pool, compared to all other participants in the game who put
fifty percent of their money into the public pool. In a follow-up survey the
researchers asked the students about their understanding of fairness. While for
all other students the concept of fairness was an important one, a large part
of the economics students either refused to answer this question or were unable
to give an understandable answer.

When the students got the opportunity to play the prisoner’s
dilemma game, which rewards participants for cheating, economics majors were
almost twice as like to cheat on their teammates as students with other majors.

The researchers also explored if economics students became
even more selfish over the course of their studies. This seems indeed to be the
case, documented by having the students play the prisoner’s dilemma game over
extended periods of time. Normally participants become more collaborative over
time, cheating less on their teammates. This effect of increasing collaboration
over time was conspicuously absent for the economics students. In an experiment
comparing economics students and students from other majors in the first and
second years, economists were significantly less fair, and more selfish than
their peers, and this effect became stronger in the second year. It seems that economists
start out more selfish than others, and that their selfish behavior gets
reinforced over time in daily interaction with other economists.

The researchers also found that economics professors are
much more stingy as charitable givers than professors in other
disciplines.In a survey answered by 576
academics, there were almost ten times as many non-givers among the economics
professors than in all other disciplines. In another natural experiment, Bruno
S. Frey, a professor of economics at the university of Zurich, investigated
the charitable behavior of 28,586 students at the university of Zurich. Each
semester students could decide if they wanted to contribute a small amount of
money towards a fund for needy students. Frey and his colleague found that in
particular students of business economics were significantly less generous than
students from other majors, and this effect stayed over the entire duration of
their studies.Frey even found that the
effect goes back to high school, as students from high schools with emphasis on
business economics were stingier than their peers. The late Stanford professor
Hal Leavitt put it succinctly,
stating that business education transforms students into “critters with lopsided
brains, icy hearts, and shrunken souls.”

Power corrupts – behavioral economists have demonstrated
this folk wisdom in a series of ingenious experiments. In a research project in
Boston and New York, researchers manipulated the feeling of power of study
participants by inviting them to stand in either an impressive posture, or in a
more humble and modest way. They then gave the participants the opportunity to
cheat on them by “accidentally” overpaying them after the “official” experiment
was over. People in the humble posture were more than twice as likely to return
the overpayment than people standing in the power position. In a second
experiment, the feeling of power was manipulated by either seating participants
at a wide and expansive desk, or giving them a small table and chair. When
study participants got an opportunity to grade their own tests, the likelihood of
cheating by correcting their own answers was again more than twice as high for
participants experiencing the “feeling of power” sitting at the wide and
expansive desk. In two further experiments the researchers compared the driving
behavior of car drivers with the size of their car. In a car simulator, if
participants got a large car seat, they drove more recklessly than when sitting
on a small and cramped car seat. In the final experiment the researchers
counted the instances of double parking in New York, which is illegal, and
encumbers other traffic participants. They found that the larger the car, the
more likely it was that drivers were willing to double park on the streets of
New York.

In addition, researchers also found
that people of higher social classes, having more power and glory, behaved less
ethical. For example, when driving on the streets, drivers of upper-class cars
were more willing to cut off other vehicles on a busy four-way intersection,
and to cut off pedestrians at a crosswalk.In further studies, participants were asked about their socioeconomic
status, as well as their willingness to lie to job applications to entice them
to accept a job. It turned out that people with higher socioeconomic status and
thus more power were more willing to cheat and to lie. In another experiment, a
feeling of power was established through psychological manipulation, by asking participants
to compare themselves against people with the least money, least education, and
least respected jobs. This put them in a mindset of power, which made them more
willing to behave unethical by taking away more candy which would otherwise
have gone to small children.

More powerful people are also more willing to cheat on their
spouses.
Conducting a survey with 1561 participants, researchers found that the higher
the socioeconomic status of a person was, the higher was both their willingness
to cheat on their partner and their actual infidelity. This was independent of gender;
more powerful women were as willing to cheat as more powerful men. In another project,
the same researchers found that power increased hypocrisy. The powerful were
stricter with others’ moral transgressions, while at the same time being more
willing to misbehave themselves. The feeling of power was again induced by
priming participants to recall experiences of low or high power. More powerful
participants were quick in condemning the cheating of others, while cheating
more themselves when playing lottery games. It seems that a position of power
goes along with a sense of entitlement.

Glory also has a dark side, as famous people have been shown
to be more narcissistic than ordinary people. In a research project
the degree of narcissism of celebrities was measured and compared against the
narcissism scores of regular people. While narcissism also has some good
aspects – for example it seems that narcissistic people are less depressed – narcissists
crave attention, are overconfident, and frequently lack empathy. For this
project, the researchers recruited 200 actors, comedians, musicians, and
reality television personalities, to fill out a survey. The celebrities had
participated in a national radio show that gives advice about drugs, sex, and
relationships. They had been invited to this show because they all appeared
frequently in the entertainment media and because of their ability to draw an
audience.These celebrities were
compared against a similarly sized sample of MBA students. The survey that was
used breaks narcissism down into the seven sub-properties authority,
exhibitionism, superiority, entitlement, exploitativeness, self-sufficiency,
and vanity. Different from the normal population, where men are more
narcissistic than women, female celebrities were even more narcissistic than
men. In particular, female celebrities excelled in exhibitionism, superiority,
and vanity. Among the different types of celebrities, reality television
personalities were the most narcissistic, while musicians were the least
narcissistic. The researchers also wanted to know if naturally narcissistic
people were drawn to the entertainment industry, or if long years in the entertainment
industry made less narcissistic participants more narcissistic. It Their
conclusion was that the length of being in the entertainment industry has no
influence on the degree of narcissism; more narcissistic people choose to work
in entertainment to start with.

On a side note, the researchers also compared the average
narcissism of their MBA students with the overall US population. They found
that also the MBA students were more narcissistic than the rest of the
population, but much less so than the celebrities.

So it seems we all should strive to be a bit less of Homo Competitivus, and more of Homo Collaborensis. However I am not sure if America is ready for it, considering that Donald Trump was nominated as the official candidate for US President, while Bernie Sanders was not?

Here are the links to the most recent versions of my two evolving booksSwarm Leadership and Homo Collaborensis: Using Collaborative Innovation Networks to Build a Better Business through Empowered Stakeholders

Thursday, August 04, 2016

Over the last year Donald Trump has been doing a brilliant
job kindling his initially highly unlikely candidacy as US Presidential
applicant. Following the principle that there is no good or bad PR, that any
news is good news as long as it is in the news, he has acted as a master
provocateur. He has been a genius in hitting the soft spots of US society,
constantly provoking increasingly broader parts of society with over 32,000 (and
rapidly growing) racist, sexist, and religiously offensive tweets.

I was curious to see how his Twitter behavior would compare
with the articulations on Twitter by his Democrat competitor for the job, Hillary
Clinton. Therefore I used Condor’s Twitter EgoFetcher (thanks, Joao, for coming
up with the idea) to collect the most recent 10,000 tweets about each candidate
on August 4, 2016 at 10.00AM. The
EgoFetcher works in four steps: in step 1 it takes the last N (for example
10,000) tweets about the search term or Twitter handle (e.g. “Donald Trump”).
Note that normally – except for an individual’s own tweets -thesearch API of Twitter only returns last week’s tweets.This is not a problem for this search, as
people send thousands of tweets about each candidate per hour. In step 2 it
constructs a network with a link from twitterer B to twitterer A if B retweets
A, or B mentions A in a tweet. In step 3 it takes the timelines of the 480 most
influential people in the search results, the influence of these people is measured
through their degree in the retweet network from step 2. For twitter users,
their timeline is all their tweets, sorted from newest to oldest. In step 4 it
adds for each tweet collected in the previous steps the first 100 retweets.

The picture below shows the combined Twitter network, with
the tweets about Donald in yellow, and about Hillary in green.

When combining the search results of the queries for “Donald
Trump” and “Hillary Clinton”, and measuring their betweenness centrality, which
in social network analysis is commonly taken as a metric of influence, Donald
easily beats Hillary. The pie chart below shows the betweenness centralities of
both the search queries for the candidates, as well as the betweenness of their Twitter personalities (realDonaldTrump and HillaryClinton).

So will Donald become the next president? Not so fast.

When looking at each of the network separately, a different
picture emerges. The picture below shows the network for Hillary at left, and
for Donald at right. The green twitterers are the ones returned in the original
search about the search term (“Hillary Clinton” or “Donald Trump”). The yellow
twitterers are the people tweeting about the most influential 480 twitterers
among the green people.

The first thing we note is that not only is the timeline
crowd of Hillary more numerous than Donald’s (18,363 people retweeting about Hillary compared to 17,295 for Donald), but they are also much more retweeted
(91,681 retweets instead of 85,890).

When calculating the six honest signals of collaboration
described for example in my new book
manuscript, the picture becomes even more pronounced.

The metrics shown above are calculated using the dynamic
social network analysis features of Condor. Activity is the total number of
tweets in the EgoFetcher network above originating from each candidate, where Hillary beats Donald.
Emotionality, sentiment, and complexity of language are calculated using the
machine learning natural language processing features of Condor, based on the language used in the Tweets. There is not much difference here, although
Hillary’s fan base uses slightly more complex language, while Donald’s
constituency is slightly more positive, which at least might be partially
explained by his hashtag #makeAmericaGreatAgain. The large difference is in
creativity, passion, and respect. Creativity is measured as average number of changes
in network position among all the twitterers, from being central to be
peripheral in the network. In earlier work we have shown that the more people
rotate in their network position, the more creative they are. Passion is
measured as the time it takes a person until he or she responds to a tweet.
Respect is measured as the time it takes all other people to respond to her or
his tweets. And in these three scores Hillary’s community beats Donald’s
handily.

I will be curious to see if increased creativity, passion and
respect translates to the election results on November 8.